Knowledge Hut

JULY 26, 2023

Consider exploring relevant Big Data Certification to deepen your knowledge and skills. What is Big Data? Big Data is the term used to describe extraordinarily massive and complicated datasets that are difficult to manage, handle, or analyze using conventional data processing methods.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

The Modern Data Company

JULY 18, 2023

High-quality data, free from errors, inconsistencies, or biases, forms the foundation for accurate analysis and reliable insights. Data products should incorporate mechanisms for data validation, cleansing, and ongoing monitoring to maintain data integrity.

Data Governance 52

Data Governance High Quality Data Government Data 52

The Modern Data Company

JULY 18, 2023

High-quality data, free from errors, inconsistencies, or biases, forms the foundation for accurate analysis and reliable insights. Data products should incorporate mechanisms for data validation, cleansing, and ongoing monitoring to maintain data integrity.

Data Governance 52

Data Governance High Quality Data Government Data 52

Monte Carlo

NOVEMBER 20, 2023

What makes data migrations complex? A data migration is the process where old datasets, perhaps resting in outdated systems, are transferred to newer, more efficient ones. Sure, you’re moving data from point A to point B, but the reality is far more nuanced. It’s a race against time, balancing speed with accuracy.

MongoDB 52

MongoDB ETL Tools Database Data 52

Monte Carlo

JULY 11, 2023

When crucial information is omitted or unavailable, the analysis or conclusions drawn from the data may be flawed or misleading. Inconsistent data: Inconsistencies within a dataset can indicate inaccuracies. This can include contradictory information or data points that do not align with established patterns or trends.

Data Cleanse 40

Data Cleanse Datasets Data Governance Government 40

Knowledge Hut

JANUARY 25, 2024

What is Data Cleaning? Data cleaning, also known as data cleansing, is the essential process of identifying and rectifying errors, inaccuracies, inconsistencies, and imperfections in a dataset. It involves removing or correcting incorrect, corrupted, improperly formatted, duplicate, or incomplete data.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

Databand.ai

JULY 3, 2023

The value of that trust is why more and more companies are introducing Chief Data Officers – with the number doubling among the top publicly traded companies between 2019 and 2021, according to PwC. In this article: Why is data reliability important? Note that data validity is sometimes considered a part of data reliability.

Data Validation 52

Data Validation Data Collection Data Machine Learning 52

Databand.ai

JULY 19, 2023

Data can come from many different sources, and in many different formats—from structured databases to unstructured documents. These sources might include external data like social media feeds, internal data like logs or reports, or even real-time data feeds from IoT (Internet of Things) devices.

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Databand.ai

JUNE 14, 2023

Ryan Yackel June 14, 2023 Understanding Data Quality Testing Data quality testing refers to the evaluation and validation of a dataset’s accuracy, consistency, completeness, and reliability. Risk mitigation: Data errors can result in expensive mistakes or even legal issues.

Amazon Web Services 52

Amazon Web Services Datasets High Quality Data ETL Tools 52

Data Engineering Weekly

OCTOBER 30, 2022

Access You Free Copy for Data Engineering Weekly Readers LinkedIn: Super Tables - The road to building reliable and discoverable data products The self-service is not free and brings challenges, as the LinkedIn data team narrates.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Monte Carlo

MAY 26, 2023

Having the data warehouse as a central source of truth can help present a more consistent view of the campaign. Screenshot of Monte Carlo’s data profiling feature, which can help with data consistency. Understand and Document the Context : Data engineers may not always have the full business context behind a dataset.

Datasets 52

Datasets Data Warehouse Data Validation Data 52

Knowledge Hut

OCTOBER 30, 2023

Data Integration: Assist in integrating data from multiple sources into Power BI, ensuring data consistency and accuracy. Data Validation: Help validate data against predefined business rules and ensure data quality. Ensure compliance with data protection regulations.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Striim

JANUARY 4, 2023

Companies need to analyze large volumes of datasets, leading to an increase in data producers and consumers within their IT infrastructures. These companies collect data from production applications and B2B SaaS tools (e.g., This data makes its way into a data repository, like a data warehouse (e.g.,

PostgreSQL 52

PostgreSQL Data Warehouse Data Lake Data 52

Knowledge Hut

OCTOBER 13, 2023

As per Microsoft, “A Power BI report is a multi-perspective view of a dataset, with visuals representing different findings and insights from that dataset. ” Reports and dashboards are the two vital components of the Power BI platform, which are used to analyze and visualize data. Data sources can change over time.

BI 52

BI Business Analyst Datasets Raw Data 52

Airbnb Tech

NOVEMBER 28, 2023

However, achieving the full data quality criteria required by Midas demands significant cross-functional investment to design, develop, validate, and maintain the necessary data assets and documentation. While this made sense for our most critical data, pursuing such rigorous standards at scale presented challenges.

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Monte Carlo

FEBRUARY 6, 2023

But in reality, a data warehouse migration to cloud solutions like Snowflake and Redshift requires a tremendous amount of preparation to be successful—from schema changes and data validation to a carefully executed QA process. What’s more, issues in the source data could even be amplified by a new, sophisticated system.

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52

Knowledge Hut

SEPTEMBER 25, 2023

To ensure effective data retrieval and processing, troubleshoot and optimize database performance. Design and maintain data models in conjunction with the data engineering team to ensure consistency and integrity of the data. Create and keep up with documentation for database schemas, data models, and SQL code.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Ascend.io

JULY 19, 2023

For one, data mesh tackles the real headaches caused by an overburdened data lake and the annoying game of tag that’s too often played between the people who make data, the ones who use it, and everyone else caught in the middle. This might involve data checks at different stages of the data lifecycle.

Data Governance 40

Data Governance Government Metadata Data 40

ProjectPro

SEPTEMBER 11, 2021

Ability to analyze huge datasets. Validate: Understanding the requirements and presenting them in a structured manner is done by a Business Analyst. The structured document is then used to understand the practical feasibility of project implementation. BRD stands for Business Requirements Document. What is BRD?

Business Analyst 52

Business Analyst Database-centric MySQL SQL 52

ProjectPro

JUNE 18, 2015

said Martha Crow, Senior VP of Global Testing at Lionbridge Big data is all the rage these days as various organizations dig through large datasets to enhance their operations and discover novel solutions to big data problems. We’re looking at the next evolution. a different way of business getting done."-

Big Data 52

Big Data Process Data Cleanse Data Analytics 52

ProjectPro

DECEMBER 22, 2016

Data Mining vs Data Analysis Data Mining Data Analysis Data mining usually does not require any hypothesis. Data analysis begins with a question or an assumption. Data Mining depends on clean and well-documented data. Data analysis involves data cleaning.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

Precisely

OCTOBER 5, 2023

Data integrity is all about building a foundation of trusted data that empowers fast, confident decisions that help you add, grow, and retain customers, move quickly and reduce costs, and manage risk and compliance – and you need data enrichment to optimize those results. Read Why is Data Enrichment Important?

Raw Data 69

Raw Data Insurance Datasets Telecommunication 69

AltexSoft

NOVEMBER 23, 2021

Metadata management — to import, document, and maintain metadata attributes such as column names, table structure, tags, etc. Dynamic data catalog — to organize data by profiling, tagging, classifying, and mapping it to business definitions so that end-users could easily find what they need. Know your data sources.

Process 69

Process Data Lake Metadata Data Warehouse 69

phData: Data Engineering

JANUARY 3, 2022

To guarantee that the latest version of a table was used when the views and materialized views were created, we used a templating library (Jinja) that would reference our configuration files for each dataset/table we had and programmatically generate the required data definition language (DDL). Databases, schemas, tables, view, etc.

IT 52

IT AWS Software Engineer Software Engineering 52

ProjectPro

AUGUST 21, 2015

Hadoop Framework works on the following two core components- 1)HDFS – Hadoop Distributed File System is the java based file system for scalable and reliable storage of large datasets. Data in HDFS is stored in the form of blocks and it operates on the Master-Slave Architecture. This data needs to be stored in HDFS.

Hadoop 40

Hadoop Big Data Metadata Java 40